Correlation Between Public Power and Frigoglass SAIC
Can any of the company-specific risk be diversified away by investing in both Public Power and Frigoglass SAIC at the same time? Although using a correlation coefficient on its own may not help to predict future stock returns, this module helps to understand the diversifiable risk of combining Public Power and Frigoglass SAIC into the same portfolio, which is an essential part of the fundamental portfolio management process.
By analyzing existing cross correlation between Public Power and Frigoglass SAIC, you can compare the effects of market volatilities on Public Power and Frigoglass SAIC and check how they will diversify away market risk if combined in the same portfolio for a given time horizon. You can also utilize pair trading strategies of matching a long position in Public Power with a short position of Frigoglass SAIC. Check out your portfolio center. Please also check ongoing floating volatility patterns of Public Power and Frigoglass SAIC.
Diversification Opportunities for Public Power and Frigoglass SAIC
0.05 | Correlation Coefficient |
Significant diversification
The 3 months correlation between Public and Frigoglass is 0.05. Overlapping area represents the amount of risk that can be diversified away by holding Public Power and Frigoglass SAIC in the same portfolio, assuming nothing else is changed. The correlation between historical prices or returns on Frigoglass SAIC and Public Power is a relative statistical measure of the degree to which these equity instruments tend to move together. The correlation coefficient measures the extent to which returns on Public Power are associated (or correlated) with Frigoglass SAIC. Values of the correlation coefficient range from -1 to +1, where. The correlation of zero (0) is possible when the price movement of Frigoglass SAIC has no effect on the direction of Public Power i.e., Public Power and Frigoglass SAIC go up and down completely randomly.
Pair Corralation between Public Power and Frigoglass SAIC
Assuming the 90 days trading horizon Public Power is expected to generate 0.34 times more return on investment than Frigoglass SAIC. However, Public Power is 2.94 times less risky than Frigoglass SAIC. It trades about -0.01 of its potential returns per unit of risk. Frigoglass SAIC is currently generating about -0.03 per unit of risk. If you would invest 1,191 in Public Power on August 28, 2024 and sell it today you would lose (9.00) from holding Public Power or give up 0.76% of portfolio value over 90 days.
| Time Period | 3 Months [change] |
| Direction | Moves Together |
| Strength | Insignificant |
| Accuracy | 95.24% |
| Values | Daily Returns |
Public Power vs. Frigoglass SAIC
Performance |
| Timeline |
| Public Power |
| Frigoglass SAIC |
Public Power and Frigoglass SAIC Volatility Contrast
Predicted Return Density |
| Returns |
Pair Trading with Public Power and Frigoglass SAIC
The main advantage of trading using opposite Public Power and Frigoglass SAIC positions is that it hedges away some unsystematic risk. Because of two separate transactions, even if Public Power position performs unexpectedly, Frigoglass SAIC can make up some of the losses. Pair trading also minimizes risk from directional movements in the market. For example, if an entire industry or sector drops because of unexpected headlines, the short position in Frigoglass SAIC will offset losses from the drop in Frigoglass SAIC's long position.| Public Power vs. Mytilineos SA | Public Power vs. Greek Organization of | Public Power vs. Hellenic Telecommunications Organization | Public Power vs. Alpha Services and |
| Frigoglass SAIC vs. Public Power | Frigoglass SAIC vs. Intralot SA Integrated | Frigoglass SAIC vs. Hellenic Petroleum SA | Frigoglass SAIC vs. Mytilineos SA |
Check out your portfolio center.Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Pattern Recognition module to use different Pattern Recognition models to time the market across multiple global exchanges.
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